Time-Sharing Reinvented: Cloud Search

Time-Sharing Reinvented: Cloud Search

Article excerpt

The cloud vies with Big Data as the go-to resource of 2014. For many organizations, moving IT to the cloud translates to reducing some costs and eliminating the headaches that on-premises system users experience.

The cloud is a reinvention of time-sharing: one of the keystones of information access that may be familiar to many. In the 1960s, users tapped into mainframes. When a scientist at NASA wanted to access a bibliographic reference to a technical article, the facility library provided a librarian to tap into a database for him. For the researcher who needed 24/7 access, bulky terminals with thermal printers allowed him to get to a network that made the digital information available.

There were variations on the time-sharing approach. Universities were able to share scarce and expensive computing resources. A petroleum company could access information on hydrocarbon exploration data. Some companies pushed boundaries in accounting-related tabulations using remote services. One thread that wove through timesharing, however, was reducing the cost of computing.

Old-School Approach

Today's cloud embraces the old-school approach of time-sharing and adds a number of up-to-date features. The core idea of using applications, memory, and servers located elsewhere is essentially intact. But the access devices include smartphones, iPads, and autonomous software.

If an organization is looking for an alternative to on-premises enterprise search, there are a number of options available. Similar to other cloud services, the offerings vary from the "box of parts" approach to a "one size fits all" solution and services that are a mix of options, features, and functions. Pricing varies as well. In fact, figuring out the cost of cloud-based enterprise search services is a difficult job. The reason is that the number of variables does not change just because the search system is deployed as a cloud service.

Amazon's solution is a beta product named Amazon CloudSearch. When the service became available in 2012, I learned in an Amazon briefing in London that I could be up and running in 1 hour for certain types of search. The company says the following:

Amazon CloudSearch is a fully-managed service in the AWS Cloud that
makes it simple and cost-effective to set up, manage, and scale a
custom search solution for your website or application. Amazon
CloudSearch now supports 34 languages and popular search features
such as highlighting, autocomplete, and geospatial search.

Amazon calls the product a "managed search service." The system "determines the size and number of search instances required to deliver low latency, high throughput search performance."

Pricing information appears on Amazon's website (amzn.to/WWJ6 Fv). Be prepared to know whether you need a small, large, extra-large, or fast food restaurant-like "double extra-large" system. A small search instance costs 10 cents an hour. The gutbuster weighs in at $1.10 an hour. The scale is logarithmic, but that is only part of the calculation you must do. You will have to figure out how many batch upload requests you need, how many requests to index documents you require, and how much data in and data out your CloudSearch instances warrant. You will then consult the EC2 pricing description (amzn.to/lfewhZn). You may want to check out Amazon's Simple Monthly Calculator (calculator.s3 .amazonaws.com/index.html).

The Downside

To estimate your fees, you will need to know details about some arcane throughput for data transfer and load balancing. In my view, the fee for CloudSearch is important information. My reaction to the pricing was that Amazon was making the cost of CloudSearch difficult to estimate, even opaque.

It is possible for you to have access to IT resources that are able to calculate the operating costs for a CloudSearch system. Amazon's cloud business may be exploding, but I would not deploy an enterprise search system using CloudSearch. …